Boundary-Layer Meteorology

, Volume 154, Issue 2, pp 189–205 | Cite as

Near-Surface Motion in the Nocturnal, Stable Boundary Layer Observed with Fibre-Optic Distributed Temperature Sensing

  • Matthias J. ZeemanEmail author
  • John S. Selker
  • Christoph K. Thomas


The evolution of cold air layers near the surface was investigated for a night with stable conditions near the surface. Spatial air temperature observations at 276 co-located vertical profiles were made using high-resolution fibre-optic based distributed temperature sensing (DTS) in a quasi three-dimensional geometry oriented along a shallow depression in the landscape and analysed for patterns in near-surface flow. Temperature stratification was observed to be interrupted by transient temperature structures on the scale of metres for which the flow direction and velocity could be quantified. The high spatial resolution and large spatial domain of the DTS revealed temperature structures in a level of detail that exceeded the capability of traditional point observations of air temperature at low wind speeds. Further, composition techniques were applied to describe wave-like motions in the opposite direction of the mean flow, at intervals of approximately 200 s (5 mHz). The DTS technique delivered tomography on a scale of tens of metres. The spatial observations at high spatial (fractions of a metre) and temporal (sec) resolution provided new opportunities for detection and quantification of surface-flow features and description of complicated scale interactions. High-resolution DTS is therefore a valuable addition to experimental research on stable and weak-wind boundary layers near the surface.


Cold-air pool Distributed temperature sensing Stable boundary layer Sub-mesoscale Surface flow Tomography Turbulence 



This research was funded by the Army Research Office, contracts W911NF-10-1-0361 and W911NF-09-1-0271, and the National Science Foundation, awards AGS 0955444. MJZ received additional support through the Helmholtz Association REKLIM initiative. The fibre-optics instrumentation was provided by the Center for Transformative Environmental Monitoring Programs (CTEMPS) funded by the National Science Foundation, award EAR 0930061. We thank Javier Orozco, Stephen Drake, Alex Smooth and Steve Cluskey (at OSU) for assistance in the field, as well as Chadi Sayde and Javier Benitez (at OSU) for support with fibre-optics. The topographic map was derived using data provided by the Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar Program and services provided by the OpenTopography Facility with support from the National Science Foundation, awards 0930731 and 0930643.


  1. Acevedo OC, Moraes OL, Degrazia GA, Medeiros LE (2006) Intermittency and the exchange of scalars in the nocturnal surface layer. Boundary-Layer Meteorol 119(1):41–55. doi: 10.1007/s10546-005-9019-3 CrossRefGoogle Scholar
  2. Anfossi D, Oettl D, Degrazia G, Goulart A (2005) An analysis of sonic anemometer observations in low wind speed conditions. Boundary-Layer Meteorol 114(1):179–203CrossRefGoogle Scholar
  3. Arya S (1999) Air pollution meteorology and dispersion. Oxford University Press, Oxford, UK, 320 ppGoogle Scholar
  4. Blackadar AK (1997) Turbulence and diffusion in the atmosphere. Springer, Berlin, 185 ppGoogle Scholar
  5. Dakin J, Pratt D, Bibby G, Ross J (1985) Distributed optical fibre Raman temperature sensor using a semiconductor light source and detector. Electron Lett 21(13):569–570. doi: 10.1049/el:19850402 CrossRefGoogle Scholar
  6. Gao W, Shaw RH, Paw UKT (1989) Observation of organized structure in turbulent flow within and above a forest canopy. Boundary-Layer Meteorol 47(1):349–377. doi: 10.1007/BF00122339 CrossRefGoogle Scholar
  7. Hausner MB, Suárez F, Glander KE, Selker JS, Tyler SW (2011) Calibrating single-ended fiber-optic Raman spectra distributed temperature sensing data. Sensors 11(11):10859–10879. doi: 10.3390/s111110859 CrossRefGoogle Scholar
  8. Keller CA, Huwald H, Vollmer MK, Wenger A, Hill M, Parlange MB, Reimann S (2011) Fiber optic distributed temperature sensing for the determination of the nocturnal atmospheric boundary layer height. Atmos Meas Tech 4(2):143–149. doi: 10.5194/amt-4-143-2011 CrossRefGoogle Scholar
  9. Mahrt L (2000) Surface heterogeneity and vertical structure of the boundary layer. Boundary-Layer Meteorol 96(1):33–62. doi: 10.1023/A:1002482332477 CrossRefGoogle Scholar
  10. Mahrt L (2010) Computing turbulent fluxes near the surface: needed improvements. Agric For Meteorol 150(4):501–509. doi: 10.1016/j.agrformet.2010.01.015 CrossRefGoogle Scholar
  11. Mahrt L, Thomas CK, Prueger JH (2009) Space-time structure of mesoscale motions in the stable boundary layer. Q J R Meteorol Soc 135(638):67–75CrossRefGoogle Scholar
  12. Mahrt L, Thomas C, Richardson S, Seaman N, Stauffer D, Zeeman M (2013) Non-stationary generation of weak turbulence for very stable and weak-wind conditions. Boundary-Layer Meteorol 147(2):179–199. doi: 10.1007/s10546-012-9782-x CrossRefGoogle Scholar
  13. Obukhov AM (1946) Turbulentnost v temperaturnoj - neodnorodnoj atmosfere. Trudy Inst Theor Geofiz AN SSSR 1:95–115Google Scholar
  14. Petrides AC, Huff J, Arik A, van de Giesen N, Kennedy AM, Thomas CK, Selker JS (2011) Shade estimation over streams using distributed temperature sensing. Water Resour Res 47(7):W07601. doi: 10.1029/2010WR009482 CrossRefGoogle Scholar
  15. Selker J, van de Giesen N, Westhoff M, Luxemburg W, Parlange MB (2006a) Fiber optics opens window on stream dynamics. Geophys Res Lett 33(24):L24401. doi: 10.1029/2006GL027979 CrossRefGoogle Scholar
  16. Selker JS, Thévenaz L, Huwald H, Mallet A, Luxemburg W, van de Giesen N, Stejskal M, Zeman J, Westhoff M, Parlange MB (2006b) Distributed fiber-optic temperature sensing for hydrologic systems. Water Resour Res 42(12):W12202. doi: 10.1029/2006WR005326 CrossRefGoogle Scholar
  17. Sorbjan Z (2006) Local structure of turbulence in stably stratified boundary layers. J Atmos Sci 63(5):1526–1537. doi: 10.1175/JAS3704.1 CrossRefGoogle Scholar
  18. Stull RB (1988) An introduction to boundary layer meteorology. Kluwer, Dordrecht, 666 ppGoogle Scholar
  19. Sun J, Mahrt L, Banta RM, Pichugina YL (2011) Turbulence regimes and turbulence intermittency in the stable boundary layer during CASES-99. J Atmos Sci 69(1):338–351. doi: 10.1175/JAS-D-11-082.1 CrossRefGoogle Scholar
  20. Taylor GI (1935) Statistical theory of turbulence. Proc R Soc Lond 151(873):421–444CrossRefGoogle Scholar
  21. Thomas C (2011) Variability of sub-canopy flow, temperature, and horizontal advection in moderately complex terrain. Boundary-Layer Meteorol 139:61–81. doi: 10.1007/s10546-010-9578-9 CrossRefGoogle Scholar
  22. Thomas C, Kennedy A, Selker J, Moretti A, Schroth M, Smoot A, Tufillaro N, Zeeman M (2012) High-resolution fibre-optic temperature sensing: a new tool to study the two-dimensional structure of atmospheric surface-layer flow. Boundary-Layer Meteorol 142(2):177–192. doi: 10.1007/s10546-011-9672-7 CrossRefGoogle Scholar
  23. Torrence C, Compo GP (1998) A practical guide to wavelet analysis. Bull Am Meteor Soc 79(1):61–78Google Scholar
  24. Tyler SW, Selker JS, Hausner MB, Hatch CE, Torgersen T, Thodal CE, Schladow SG (2009) Environmental temperature sensing using Raman spectra DTS fiber-optic methods. Water Resour Res 45(4). doi: 10.1029/2008WR007052
  25. van de Giesen N, Steele-Dunne SC, Jansen J, Hoes O, Hausner MB, Tyler S, Selker J (2012) Double-ended calibration of fiber-optic Raman spectra distributed temperature sensing data. Sensors 12(5):5471–5485. doi: 10.3390/s120505471 CrossRefGoogle Scholar
  26. Zeeman MJ (2013) High-resolution air temperature observations near the surface using fiber-optic distributed temperature sensing. ZENODO. doi: 10.5281/zenodo.7611

Copyright information

© Springer Science+Business Media Dordrecht (outside the USA) 2014

Authors and Affiliations

  • Matthias J. Zeeman
    • 1
    • 2
    Email author
  • John S. Selker
    • 3
  • Christoph K. Thomas
    • 1
  1. 1.College of Earth, Ocean and Atmospheric SciencesOregon State UniversityCorvallisUSA
  2. 2.IMK–IFUKarlsruhe Institute of TechnologyGarmisch-PartenkirchenGermany
  3. 3.Department of Biological and Ecological EngineeringOregon State UniversityCorvallisUSA

Personalised recommendations